- name
- walter-competitor
- version
- 2.0.0
- description
- 亚马逊竞品流量攻防智能分析。自动发现竞品、分析流量结构、识别弱点、生成攻击矩阵。无需手动提供ASIN，全自动竞品情报获取。
亚马逊竞品流量攻防智能分析
核心能力
自动发现竞品 → 流量结构分析 → 弱点挖掘 → 攻击矩阵生成
全自动情报获取 → 智能攻防策略 → 可执行投放方案用户交互（极简）
输入（2个参数）
必需:
keyword: "women active shorts" # 品类关键词
my_price: 32.0 # 我的产品售价
可选:
my_margin: 0.30 # 毛利率（默认30%）输出
竞品流量攻防完整方案
├── 竞品情报（自动发现Top 5）
├── 流量结构分析
├── 关键词攻防矩阵
├── 竞品弱点地图
├── 攻击矩阵（P0/P1/P2）
└── 预算与ROI方案分析流程
Step 1: 自动发现竞品（30秒）
系统自动：
# 1. 获取竞品列表
competitors = data_layer.get_competitor_lookup(keyword)
# 2. 筛选Top 5（按销量/相关性）
top_competitors = filter_top_competitors(competitors, n=5)
# 3. 并行获取详细情报
with ThreadPoolExecutor(max_workers=5) as executor:
for asin in top_competitors:
executor.submit(data_layer.get_complete_competitor_intelligence, asin)输出示例：
[Auto-Discover Competitors] 30 seconds
Found 5 core competitors for "women active shorts":
1. ASIN: B071WV2SRC (CRZ YOGA)
Sales: ~3,200/month | Price: $28.99 | Rating: 4.5
Traffic Keywords: 15 | Weakness: No brand ads [WARNING]
2. ASIN: B08KHQY9DV (BALEAF)
Sales: ~2,800/month | Price: $25.99 | Rating: 4.2
Traffic Keywords: 22 | Weakness: Low rating, many bad reviews [WARNING]
3. ASIN: B0CBCWHC6P (New Brand)
Sales: ~1,500/month | Price: $32.99 | Rating: 4.6
Traffic Keywords: 8 | Weakness: Few keywords, under-promoted [WARNING]
[View Details] [Adjust Range] [Add Custom ASIN]Step 2: 流量结构全景（1分钟）
分析每个竞品的流量来源：
[Traffic Structure Analysis]
CompA CompB CompC Market Avg
Organic Search ████████ 45% ██████ 35% ████ 20% 35%
SP Ads ████ 20% ████████ 40% ██ 10% 25%
Brand Ads ██ 10% ████ 20% █ 5% 12%
Video Ads █ 5% ██ 10% █ 5% 7%
AC Recommended ████ 15% ████ 15% ████████ 50% 18%
Other ███ 5% ██ 5% ██ 10% 8%
Insights:
• CompA: Relies on organic, low ad spend → Opportunity: Increase ads to steal traffic
• CompB: SP ads 40% → Learn their keyword strategy
• CompC: AC 50% → High conversion, focus targetStep 3: 关键词攻防矩阵（2分钟）
[Keyword Battle Matrix] Top 50 Keywords
High-Value Attack Targets (Competitors have but weak coverage):
┌─────────────────────┬──────────┬────────┬─────────┬──────────┐
│ Keyword │ Volume │ CompA │ CompB │ Action │
├─────────────────────┼──────────┼────────┼─────────┼──────────┤
│ quick dry shorts │ 12,500 │ [P3] │ [X] │ [ATTACK] │
│ athletic shorts women│ 8,900 │ [P5] │ [P8] │ [ATTACK] │
│ yoga shorts pocket │ 5,600 │ [X] │ [X] │ [ATTACK] │
│ running shorts 5 inch│ 4,200 │ [P12] │ [X] │ [ATTACK] │
└─────────────────────┴──────────┴────────┴─────────┴──────────┘
Your Advantage Keywords (No competitor coverage):
• "anti-chafe shorts" - Volume 2,100, no competitors [CHECK]
• "high waist workout" - Volume 1,800, only 1 competitor [CHECK]
Defensive Keywords (Your core words to protect):
• "women active shorts" - All competitors bidding [WARNING]Step 4: CPA/ACOS Analysis（自动计算）
[Ad ROI Calculation] Based on your price $32, margin 30%
Target CPA: $9.6 (Price × Margin)
Keyword Bidding Recommendations:
┌─────────────────────┬────────┬────────┬────────┬────────┐
│ Keyword │ Bid │ Est.CVR│ Est.CPA│ P&L │
├─────────────────────┼────────┼────────┼────────┼────────┤
│ quick dry shorts │ $1.80 │ 8% │ $22.5 │ [LOSS] │
│ athletic shorts │ $1.20 │ 12% │ $10.0 │ [LOW] │
│ yoga shorts pocket │ $0.90 │ 15% │ $6.0 │ [PROFIT]│
│ workout shorts │ $1.50 │ 10% │ $15.0 │ [LOSS] │
└─────────────────────┴────────┴────────┴────────┴────────┘
Traffic Light System:
[GREEN] Profit: 3 keywords, scale up
[YELLOW] Marginal: 5 keywords, optimize conversion
[RED] Loss: 2 keywords, pause or reduce bidStep 5: 竞品弱点挖掘（1分钟）
[Competitor Weakness Map]
Competitor A (B071WV2SRC - CRZ YOGA):
├─ Traffic: Only 15 keywords, no brand ads
├─ Rating: 4.5, but 18% reviews mention "pilling"
├─ Price: $28.99, reduced 3 times recently (price war)
└─ VOC: Users complain "pockets too small"
[Attack Strategy] Emphasize "anti-pilling" + "large pockets"
Competitor B (B08KHQY9DV - BALEAF):
├─ Traffic: Over-relies on SP ads (40%), weak organic
├─ Rating: 4.2, 12% return rate (industry avg 8%)
├─ Product: Thin fabric, see-through issues
└─ Service: Slow support, poor review handling
[Attack Strategy] Emphasize "quality" + "service", steal dissatisfied users
Competitor C (B0CBCWHC6P - New Brand):
├─ Traffic: Only 8 keywords, severely under-promoted
├─ Strength: 4.6 rating, good product but unknown
└─ Opportunity: Copy their successful keywords
[Attack Strategy] Learn their path, increase promotionStep 6: 攻击矩阵生成（核心输出）
[Traffic Battle Plan]
═══════════════════════════════════════════════════════════════
P0 - Execute Immediately (High ROI, Quick Results)
═══════════════════════════════════════════════════════════════
Target 1: Steal CompA's "quick dry shorts" traffic
├─ Action: SP exact match, bid $1.50
├─ Budget: $50/day
├─ Expected: 30 clicks/day, 3 conversions
├─ ROI: +25%
└─ Timeline: Launch now
Target 2: Capture CompB's lost customers
├─ Action: Brand defense ads, keyword "BALEAF alternative"
├─ Budget: $30/day
├─ Expected: 15 clicks/day, 2 conversions
├─ ROI: +40% (high-quality competitor users)
└─ Timeline: Launch now
Target 3: Capture empty keyword "yoga shorts pocket"
├─ Action: SP+SB simultaneous bidding
├─ Budget: $40/day
├─ Expected: 25 clicks/day, 4 conversions
├─ ROI: +35%
└─ Timeline: Launch now
P0 Total Budget: $120/day
P0 Expected Return: +9 orders/day, $288 ad sales, $43 profit
═══════════════════════════════════════════════════════════════
P1 - Short-term (1-2 Weeks)
═══════════════════════════════════════════════════════════════
Target 1: Improve organic ranking
├─ Action: Optimize listing keywords, add "anti-chafe" differentiation
├─ Budget: $0 (optimization cost)
└─ Timeline: Complete this week
Target 2: Video ad test
├─ Action: SBV video ad, show "anti-pilling test"
├─ Budget: $60/day test
└─ Timeline: Launch within 2 weeks
═══════════════════════════════════════════════════════════════
P2 - Long-term Layout (1 Month)
═══════════════════════════════════════════════════════════════
Target 1: Brand defense
├─ Action: Bid on your own brand keywords
├─ Budget: $20/day
└─ Timeline: Within 1 month
Target 2: Related traffic
├─ Action: Target complementary products (yoga mats, sports bras)
├─ Budget: $40/day
└─ Timeline: Within 1 monthStep 7: 预算与ROI方案
[Ad Budget Plans]
Conservative Plan (Daily $120):
├─ P0 Attack: $120/day
├─ Expected Daily Orders: +9
├─ Expected Daily Sales: $288
├─ Expected Daily Profit: $43
└─ Payback: Immediate
Standard Plan (Daily $200):
├─ P0 Attack: $120/day
├─ P1 Test: $60/day
├─ P2 Layout: $20/day
├─ Expected Daily Orders: +15
├─ Expected Daily Sales: $480
├─ Expected Daily Profit: $62
└─ Payback: Immediate
Aggressive Plan (Daily $350):
├─ P0 Attack: $150/day (increased)
├─ P1 Test: $100/day (multi-keyword)
├─ P2 Layout: $100/day (fast positioning)
├─ Expected Daily Orders: +28
├─ Expected Daily Sales: $896
├─ Expected Daily Profit: $98
└─ Risk: Monitor ACOS closely
[Recommendation] Start with conservative, scale up after ROI validation技术实现
竞品自动发现算法
def auto_discover_competitors(keyword: str, n: int = 5) -> List[str]:
"""Auto-discover core competitors"""
# 1. Get competitor list
result = data_layer.get_competitor_lookup(keyword)
competitors = result.get("data", {}).get("items", [])
# 2. Score and rank
scored_competitors = []
for comp in competitors:
score = 0
score += comp.get("monthlySales", 0) * 0.4
score += comp.get("relevanceScore", 0) * 0.3
score += comp.get("ratings", 0) * 0.0001 * 0.2
price_diff = abs(comp.get("price", 0) - my_price)
score += max(0, (50 - price_diff)) * 0.1
scored_competitors.append((comp["asin"], score))
# 3. Return Top N
scored_competitors.sort(key=lambda x: x[1], reverse=True)
return [asin for asin, _ in scored_competitors[:n]]弱点挖掘算法
def mine_weaknesses(competitor_data: dict) -> List[dict]:
"""Mine competitor weaknesses"""
weaknesses = []
# Traffic weakness
traffic = competitor_data.get("traffic_analysis", {})
if traffic.get("total_traffic_keywords", 0) < 20:
weaknesses.append({
"type": "low_traffic_diversity",
"severity": "high",
"description": f"Only {traffic['total_traffic_keywords']} traffic keywords",
"attack_opportunity": "Capture their missing keywords"
})
# VOC weakness
voc = competitor_data.get("voc_analysis", {})
pain_points = voc.get("pain_points", [])
if len(pain_points) > 5:
top_pain = pain_points[0]
weaknesses.append({
"type": "voc_pain_point",
"severity": "high",
"description": top_pain["theme"],
"attack_opportunity": f"Emphasize '{top_pain['theme']}' solution"
})
return weaknesses依赖
unified_data_layer_v2.py- 统一数据层sellersprite_mcp.py- MCP客户端- SellerSprite API access
版本
V2 - 2026-04-12
- Added auto-competitor discovery
- Implemented traffic structure analysis
- Added keyword battle matrix
- Generated P0/P1/P2 attack plans